Various systems and data sources exist within the semiconductor manufacturing sector for various different tasks, and similar systems exist within other manufacturing sectors. Data that is obtained from components that perform these separate tasks is not, however, well integrated. Still further, the sheer volume of data that within the fabrication of integrated circuits is immense, leading to difficulty in determining which data to use and how to affect decisions.
FIG. 1 illustrates a traditional approach for analyzing data. In such an approach, a user might attempt to store all of the data in one large database. Then use an extremely expensive server to grab relevant data and correlate all of the data to the response of interest. This leads to frustrated users because (1) due to the sheer size of the data, correlations are bound to appear either just by pure chance or because even micro-sized impacts get magnified to statistical significant just based on data size (2) the cost in time and equipment of maintaining and developing such a system is immense.